{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2c83651f-fd00-4f93-9ef3-0959b2be7538",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>parent</th>\n",
       "      <th>address</th>\n",
       "      <th>pname</th>\n",
       "      <th>cityname</th>\n",
       "      <th>type</th>\n",
       "      <th>typecode</th>\n",
       "      <th>shopinfo</th>\n",
       "      <th>childtype</th>\n",
       "      <th>adname</th>\n",
       "      <th>name</th>\n",
       "      <th>location</th>\n",
       "      <th>tel</th>\n",
       "      <th>lng</th>\n",
       "      <th>lat</th>\n",
       "      <th>geometry</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>B001B0IZY1</td>\n",
       "      <td>[ ]</td>\n",
       "      <td>八一路299号</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>武汉市</td>\n",
       "      <td>科教文化服务;学校;高等院校</td>\n",
       "      <td>141201</td>\n",
       "      <td>0</td>\n",
       "      <td>[ ]</td>\n",
       "      <td>武昌区</td>\n",
       "      <td>武汉大学</td>\n",
       "      <td>114.364339,30.536334</td>\n",
       "      <td>027-68754231</td>\n",
       "      <td>114.364339</td>\n",
       "      <td>30.536334</td>\n",
       "      <td>POINT (114.36434 30.53633)</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B001B06EAF</td>\n",
       "      <td>B001B16LUR</td>\n",
       "      <td>友谊大道368号(湖北大学地铁站D口步行60米)</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>武汉市</td>\n",
       "      <td>科教文化服务;学校;高等院校</td>\n",
       "      <td>141201</td>\n",
       "      <td>0</td>\n",
       "      <td>309</td>\n",
       "      <td>武昌区</td>\n",
       "      <td>湖北大学武昌校区</td>\n",
       "      <td>114.334121,30.57687</td>\n",
       "      <td>027-88664102</td>\n",
       "      <td>114.334121</td>\n",
       "      <td>30.576870</td>\n",
       "      <td>POINT (114.33412 30.57687)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>B001B06U1W</td>\n",
       "      <td>[ ]</td>\n",
       "      <td>东湖路115号(中南医院地铁站D口步行110米)</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>武汉市</td>\n",
       "      <td>科教文化服务;学校;高等院校</td>\n",
       "      <td>141201</td>\n",
       "      <td>0</td>\n",
       "      <td>[ ]</td>\n",
       "      <td>武昌区</td>\n",
       "      <td>武汉大学医学部</td>\n",
       "      <td>114.353884,30.554086</td>\n",
       "      <td>027-68758689</td>\n",
       "      <td>114.353884</td>\n",
       "      <td>30.554086</td>\n",
       "      <td>POINT (114.35388 30.55409)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>B001B0IFVJ</td>\n",
       "      <td>[ ]</td>\n",
       "      <td>白沙洲大道519号</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>武汉市</td>\n",
       "      <td>科教文化服务;学校;高等院校</td>\n",
       "      <td>141201</td>\n",
       "      <td>0</td>\n",
       "      <td>[ ]</td>\n",
       "      <td>武昌区</td>\n",
       "      <td>湖北财税职业学院</td>\n",
       "      <td>114.298612,30.515271</td>\n",
       "      <td>027-88116071;027-88117970</td>\n",
       "      <td>114.298612</td>\n",
       "      <td>30.515271</td>\n",
       "      <td>POINT (114.29861 30.51527)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>B001B0I9T0</td>\n",
       "      <td>[ ]</td>\n",
       "      <td>武珞路114号</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>武汉市</td>\n",
       "      <td>科教文化服务;学校;高等院校</td>\n",
       "      <td>141201</td>\n",
       "      <td>0</td>\n",
       "      <td>[ ]</td>\n",
       "      <td>武昌区</td>\n",
       "      <td>中南财经政法大学首义校区</td>\n",
       "      <td>114.313162,30.537365</td>\n",
       "      <td>[ ]</td>\n",
       "      <td>114.313162</td>\n",
       "      <td>30.537365</td>\n",
       "      <td>POINT (114.31316 30.53736)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>305</th>\n",
       "      <td>B001B1BP8P</td>\n",
       "      <td>B001B06EAF</td>\n",
       "      <td>学院路368号(湖北大学地铁站E口步行440米)</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>武汉市</td>\n",
       "      <td>科教文化服务;学校;高等院校</td>\n",
       "      <td>141201</td>\n",
       "      <td>0</td>\n",
       "      <td>309</td>\n",
       "      <td>武昌区</td>\n",
       "      <td>湖北大学-培训学院</td>\n",
       "      <td>114.330376,30.576231</td>\n",
       "      <td>[ ]</td>\n",
       "      <td>114.330376</td>\n",
       "      <td>30.576231</td>\n",
       "      <td>POINT (114.33038 30.57623)</td>\n",
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       "    <tr>\n",
       "      <th>306</th>\n",
       "      <td>B001B0JG3X</td>\n",
       "      <td>B001B06U1W</td>\n",
       "      <td>东湖路115号武汉大学医学部</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>武汉市</td>\n",
       "      <td>科教文化服务;学校;高等院校</td>\n",
       "      <td>141201</td>\n",
       "      <td>0</td>\n",
       "      <td>309</td>\n",
       "      <td>武昌区</td>\n",
       "      <td>武汉大学医学部国际学术交流中心</td>\n",
       "      <td>114.355538,30.551182</td>\n",
       "      <td>027-67819988</td>\n",
       "      <td>114.355538</td>\n",
       "      <td>30.551182</td>\n",
       "      <td>POINT (114.35554 30.55118)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>307</th>\n",
       "      <td>B001B0IRVC</td>\n",
       "      <td>B001B0IZY1</td>\n",
       "      <td>八一路299号文澜路武汉大学</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>武汉市</td>\n",
       "      <td>科教文化服务;学校;高等院校</td>\n",
       "      <td>141201</td>\n",
       "      <td>0</td>\n",
       "      <td>309</td>\n",
       "      <td>武昌区</td>\n",
       "      <td>武汉大学国际教育中心</td>\n",
       "      <td>114.360843,30.544172</td>\n",
       "      <td>[ ]</td>\n",
       "      <td>114.360843</td>\n",
       "      <td>30.544172</td>\n",
       "      <td>POINT (114.36084 30.54417)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>308</th>\n",
       "      <td>B001B0IG2Z</td>\n",
       "      <td>B001B0IZY1</td>\n",
       "      <td>珞珈山16号武汉大学</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>武汉市</td>\n",
       "      <td>科教文化服务;学校;高等院校</td>\n",
       "      <td>141201</td>\n",
       "      <td>0</td>\n",
       "      <td>309</td>\n",
       "      <td>武昌区</td>\n",
       "      <td>武汉大学法学院</td>\n",
       "      <td>114.3712,30.538789</td>\n",
       "      <td>027-68752932;027-68752917;027-68756607</td>\n",
       "      <td>114.371200</td>\n",
       "      <td>30.538789</td>\n",
       "      <td>POINT (114.3712 30.53879)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>309</th>\n",
       "      <td>B001B0IFRA</td>\n",
       "      <td>B001B06U1W</td>\n",
       "      <td>中南医院地铁站D口步行380米</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>武汉市</td>\n",
       "      <td>科教文化服务;学校;高等院校</td>\n",
       "      <td>141201</td>\n",
       "      <td>0</td>\n",
       "      <td>309</td>\n",
       "      <td>武昌区</td>\n",
       "      <td>武汉大学基础医学实验教学中心</td>\n",
       "      <td>114.356757,30.555513</td>\n",
       "      <td>027-87331773</td>\n",
       "      <td>114.356757</td>\n",
       "      <td>30.555513</td>\n",
       "      <td>POINT (114.35676 30.55551)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>310 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id      parent                   address pname cityname  \\\n",
       "0    B001B0IZY1         [ ]                   八一路299号   湖北省      武汉市   \n",
       "1    B001B06EAF  B001B16LUR  友谊大道368号(湖北大学地铁站D口步行60米)   湖北省      武汉市   \n",
       "2    B001B06U1W         [ ]  东湖路115号(中南医院地铁站D口步行110米)   湖北省      武汉市   \n",
       "3    B001B0IFVJ         [ ]                 白沙洲大道519号   湖北省      武汉市   \n",
       "4    B001B0I9T0         [ ]                   武珞路114号   湖北省      武汉市   \n",
       "..          ...         ...                       ...   ...      ...   \n",
       "305  B001B1BP8P  B001B06EAF  学院路368号(湖北大学地铁站E口步行440米)   湖北省      武汉市   \n",
       "306  B001B0JG3X  B001B06U1W            东湖路115号武汉大学医学部   湖北省      武汉市   \n",
       "307  B001B0IRVC  B001B0IZY1            八一路299号文澜路武汉大学   湖北省      武汉市   \n",
       "308  B001B0IG2Z  B001B0IZY1                珞珈山16号武汉大学   湖北省      武汉市   \n",
       "309  B001B0IFRA  B001B06U1W           中南医院地铁站D口步行380米   湖北省      武汉市   \n",
       "\n",
       "               type typecode  shopinfo childtype adname             name  \\\n",
       "0    科教文化服务;学校;高等院校   141201         0       [ ]    武昌区             武汉大学   \n",
       "1    科教文化服务;学校;高等院校   141201         0       309    武昌区         湖北大学武昌校区   \n",
       "2    科教文化服务;学校;高等院校   141201         0       [ ]    武昌区          武汉大学医学部   \n",
       "3    科教文化服务;学校;高等院校   141201         0       [ ]    武昌区         湖北财税职业学院   \n",
       "4    科教文化服务;学校;高等院校   141201         0       [ ]    武昌区     中南财经政法大学首义校区   \n",
       "..              ...      ...       ...       ...    ...              ...   \n",
       "305  科教文化服务;学校;高等院校   141201         0       309    武昌区        湖北大学-培训学院   \n",
       "306  科教文化服务;学校;高等院校   141201         0       309    武昌区  武汉大学医学部国际学术交流中心   \n",
       "307  科教文化服务;学校;高等院校   141201         0       309    武昌区       武汉大学国际教育中心   \n",
       "308  科教文化服务;学校;高等院校   141201         0       309    武昌区          武汉大学法学院   \n",
       "309  科教文化服务;学校;高等院校   141201         0       309    武昌区   武汉大学基础医学实验教学中心   \n",
       "\n",
       "                 location                                     tel         lng  \\\n",
       "0    114.364339,30.536334                            027-68754231  114.364339   \n",
       "1     114.334121,30.57687                            027-88664102  114.334121   \n",
       "2    114.353884,30.554086                            027-68758689  114.353884   \n",
       "3    114.298612,30.515271               027-88116071;027-88117970  114.298612   \n",
       "4    114.313162,30.537365                                     [ ]  114.313162   \n",
       "..                    ...                                     ...         ...   \n",
       "305  114.330376,30.576231                                     [ ]  114.330376   \n",
       "306  114.355538,30.551182                            027-67819988  114.355538   \n",
       "307  114.360843,30.544172                                     [ ]  114.360843   \n",
       "308    114.3712,30.538789  027-68752932;027-68752917;027-68756607  114.371200   \n",
       "309  114.356757,30.555513                            027-87331773  114.356757   \n",
       "\n",
       "           lat                    geometry  \n",
       "0    30.536334  POINT (114.36434 30.53633)  \n",
       "1    30.576870  POINT (114.33412 30.57687)  \n",
       "2    30.554086  POINT (114.35388 30.55409)  \n",
       "3    30.515271  POINT (114.29861 30.51527)  \n",
       "4    30.537365  POINT (114.31316 30.53736)  \n",
       "..         ...                         ...  \n",
       "305  30.576231  POINT (114.33038 30.57623)  \n",
       "306  30.551182  POINT (114.35554 30.55118)  \n",
       "307  30.544172  POINT (114.36084 30.54417)  \n",
       "308  30.538789   POINT (114.3712 30.53879)  \n",
       "309  30.555513  POINT (114.35676 30.55551)  \n",
       "\n",
       "[310 rows x 16 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 点地图\n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "# 设置字体为Times New Roman\n",
    "plt.rcParams['font.sans-serif'] = ['Times New Roman']\n",
    "plt.rcParams['axes.unicode_minus'] = False# 显示负号\n",
    "# 读取包含点数据的地理数据文件\n",
    "gdf = gpd.read_file(r'data\\武昌区_高等院校.geojson')\n",
    "gdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ecd9691a-707c-4dcf-8b9f-af52409ea889",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 进行核密度估计\n",
    "kde = gdf.plot(kind='kde', cmap='Reds', figsize=(10, 8))\n",
    "\n",
    "# 设置图形标题和坐标轴标签\n",
    "plt.title('Kernel Density Analysis of Universities')\n",
    "plt.xlabel('Longitude')\n",
    "plt.ylabel('Latitude')\n",
    "\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "dcefd60a-6854-4b6b-8790-92d8d6911367",
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import json\n",
    "poi_search_url = \"http://restapi.amap.com/v3/place/text\"\n",
    "def get_poi_data(keyword, city, api_key):\n",
    "    i = 1\n",
    "    poilist = []\n",
    "    while True:\n",
    "        result = get_poi_page(keyword, city, api_key, i)\n",
    "        try:\n",
    "            result = json.loads(result)\n",
    "            # 在这里添加对返回数据更全面的验证逻辑，例如判断是否包含必要的键等\n",
    "            if 'count' in result and result['count'] == '0':\n",
    "                break\n",
    "            handle_poi_list(poilist, result)\n",
    "            i += 1\n",
    "        except json.JSONDecodeError as e:\n",
    "            print(f\"解析JSON数据出错: {e}，可能请求出现问题，当前页码: {i}\")\n",
    "            break\n",
    "    return poilist\n",
    "\n",
    "def get_poi_page(keyword, city, api_key, page):\n",
    "    req_url = poi_search_url + \"?key=\" + api_key + '&extensions=all&keywords=' + keyword + '&city=' + city + '&citylimit=true' + '&offset=25' + '&page=' + str(page) + '&output=json'\n",
    "    data = ''\n",
    "    with requests.get(req_url) as f:\n",
    "        if f.status_code == 200:  # 判断请求是否成功返回，状态码200表示成功\n",
    "            data = f.text\n",
    "        else:\n",
    "            print(f\"请求高德地图 API 失败，状态码: {f.status_code}\")\n",
    "            return None  # 如果请求失败，直接返回None避免后续解析出错\n",
    "    return data\n",
    "\n",
    "# def handle_poi_list(poilist, result):\n",
    "#     print(result)  # 打印接收到的数据，查看具体结构\n",
    "#     pois = result['pois']\n",
    "#     for i in range(len(pois)):\n",
    "#         poilist.append(pois[i])\n",
    "\n",
    "def handle_poi_list(poilist, result):\n",
    "    # 根据实际数据结构，判断使用合适的键来获取高校相关信息\n",
    "    if 'places' in result:\n",
    "        pois = result['places']\n",
    "        for i in range(len(pois)):\n",
    "            poilist.append(pois[i])\n",
    "    else:\n",
    "        print(\"数据结构中不存在预期的高校信息键，无法提取相关数据\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4ab69040-0510-4f84-b166-ac0c3d9c009f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "def preprocess_data(poi_data):\n",
    "    data = []\n",
    "    for poi in poi_data:\n",
    "        name = poi['name']\n",
    "        location = poi['location'].split(',')\n",
    "        lng = float(location[0])\n",
    "        lat = float(location[1])\n",
    "        data.append([name, lng, lat])\n",
    "    df = pd.DataFrame(data, columns=['name', 'longitude', 'latitude'])\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3984d2a7-1878-4797-b19f-5938ca671301",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "from shapely.geometry import Point\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "def kernel_density_analysis(df):\n",
    "    # 创建GeoDataFrame\n",
    "    geometry = [Point(xy) for xy in zip(df['longitude'], df['latitude'])]\n",
    "    gdf = gpd.GeoDataFrame(df, geometry=geometry)\n",
    "    gdf\n",
    "    # 进行核密度估计\n",
    "    kde = gdf.plot(kind='kde', cmap='Reds', figsize=(10, 8))\n",
    "\n",
    "    # 设置图形标题和坐标轴标签\n",
    "    plt.title('Kernel Density Analysis of Universities')\n",
    "    plt.xlabel('Longitude')\n",
    "    plt.ylabel('Latitude')\n",
    "\n",
    "    # 显示图形\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "65e51708-0531-400f-9b3e-194638bf3410",
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'pysal'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[6], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpysal\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mesda\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m mean_center, directionalanddistance\n\u001b[0;32m      3\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mexploratory_spatial_data_analysis\u001b[39m(df):\n\u001b[0;32m      4\u001b[0m     \u001b[38;5;66;03m# 计算平均中心\u001b[39;00m\n\u001b[0;32m      5\u001b[0m     x_mean, y_mean \u001b[38;5;241m=\u001b[39m mean_center(df[[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlongitude\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlatitude\u001b[39m\u001b[38;5;124m'\u001b[39m]])\n",
      "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'pysal'"
     ]
    }
   ],
   "source": [
    "from pysal.esda import mean_center, directionalanddistance\n",
    "\n",
    "def exploratory_spatial_data_analysis(df):\n",
    "    # 计算平均中心\n",
    "    x_mean, y_mean = mean_center(df[['longitude', 'latitude']])\n",
    "\n",
    "    # 计算标准差椭圆\n",
    "    coords = df[['longitude', 'latitude']].values\n",
    "    ellipse = directionalanddistance(coords)\n",
    "\n",
    "    # 绘制数据点和平均中心\n",
    "    fig, ax = plt.subplots(figsize=(10, 8))\n",
    "    df.plot(ax=ax, color='blue', markersize=10, label='Universities')\n",
    "    ax.scatter(x_mean, y_mean, color='red', marker='*', s=200, label='Mean Center')\n",
    "\n",
    "    # 绘制标准差椭圆\n",
    "    ellipse_x, ellipse_y = ellipse[0], ellipse[1]\n",
    "    ax.plot(ellipse_x, ellipse_y, color='green', label='Standard Deviational Ellipse')\n",
    "\n",
    "    # 设置图形标题和坐标轴标签\n",
    "    plt.title('Exploratory Spatial Data Analysis of Universities')\n",
    "    plt.xlabel('Longitude')\n",
    "    plt.ylabel('Latitude')\n",
    "\n",
    "    # 添加图例\n",
    "    plt.legend()\n",
    "\n",
    "    # 显示图形\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c4231fe0-6e70-42cf-818b-20ad70d9c811",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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'email': [], 'timestamp': '2024-09-22 09:39:31', 'website': [], 'address': '东湖路115号(中南医院地铁站D口步行400米)', 'adcode': '420106', 'pname': '湖北省', 'biz_type': [], 'cityname': '武汉市', 'postcode': [], 'match': '0', 'business_area': '水果湖', 'indoor_data': {'cmsid': [], 'truefloor': [], 'cpid': [], 'floor': []}, 'childtype': '309', 'exit_location': [], 'name': '武汉大学药学院', 'location': '114.356496,30.554953', 'shopid': [], 'navi_poiid': 'H50F018003_58848', 'groupbuy_num': '0'}, {'parent': 'B001B0IZY1', 'distance': [], 'pcode': '420000', 'importance': [], 'biz_ext': {'cost': [], 'rating': []}, 'recommend': '0', 'type': '科教文化服务;科研机构;科研机构', 'photos': [{'title': [], 'url': 'http://store.is.autonavi.com/showpic/2e4e77ab07204e17d8615f8a65b81dc4'}, {'title': [], 'url': 'http://store.is.autonavi.com/showpic/f53e0d51a537789d1d5fb297ac276527'}], 'discount_num': '0', 'gridcode': '4514625802', 'typecode': '141300', 'shopinfo': '0', 'poiweight': [], 'citycode': '027', 'adname': '武昌区', 'children': [], 'alias': [], 'tel': '027-68772105;027-68776130', 'id': 'B001B1DGSP', 'tag': [], 'event': [], 'entr_location': '114.359772,30.542567', 'indoor_map': '0', 'email': [], 'timestamp': '2024-02-01 23:21:20', 'website': [], 'address': '八一路299号松园中路武汉大学', 'adcode': '420106', 'pname': '湖北省', 'biz_type': [], 'cityname': '武汉市', 'postcode': [], 'match': '0', 'business_area': '珞珈山', 'indoor_data': {'cmsid': [], 'truefloor': [], 'cpid': [], 'floor': []}, 'childtype': '309', 'exit_location': [], 'name': '武汉大学科学技术发展研究院', 'location': '114.359734,30.542614', 'shopid': [], 'navi_poiid': 'H50F018003_102674', 'groupbuy_num': '0'}], 'status': '1', 'info': 'OK'}\n",
      "{'status': '0', 'info': 'CUQPS_HAS_EXCEEDED_THE_LIMIT', 'infocode': '10021'}\n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "'pois'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[20], line 9\u001b[0m\n\u001b[0;32m      6\u001b[0m city \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m武昌区\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m      8\u001b[0m \u001b[38;5;66;03m# 获取POI数据\u001b[39;00m\n\u001b[1;32m----> 9\u001b[0m poi_data \u001b[38;5;241m=\u001b[39m \u001b[43mget_poi_data\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkeyword\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcity\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mapi_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     11\u001b[0m \u001b[38;5;66;03m# 数据预处理\u001b[39;00m\n\u001b[0;32m     12\u001b[0m df \u001b[38;5;241m=\u001b[39m preprocess_data(poi_data)\n",
      "Cell \u001b[1;32mIn[19], line 14\u001b[0m, in \u001b[0;36mget_poi_data\u001b[1;34m(keyword, city, api_key)\u001b[0m\n\u001b[0;32m     12\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcount\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;129;01min\u001b[39;00m result \u001b[38;5;129;01mand\u001b[39;00m result[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcount\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m0\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[0;32m     13\u001b[0m         \u001b[38;5;28;01mbreak\u001b[39;00m\n\u001b[1;32m---> 14\u001b[0m     \u001b[43mhandle_poi_list\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpoilist\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mresult\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     15\u001b[0m     i \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m     16\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m json\u001b[38;5;241m.\u001b[39mJSONDecodeError \u001b[38;5;28;01mas\u001b[39;00m e:\n",
      "Cell \u001b[1;32mIn[19], line 34\u001b[0m, in \u001b[0;36mhandle_poi_list\u001b[1;34m(poilist, result)\u001b[0m\n\u001b[0;32m     32\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mhandle_poi_list\u001b[39m(poilist, result):\n\u001b[0;32m     33\u001b[0m     \u001b[38;5;28mprint\u001b[39m(result)  \u001b[38;5;66;03m# 打印接收到的数据，查看具体结构\u001b[39;00m\n\u001b[1;32m---> 34\u001b[0m     pois \u001b[38;5;241m=\u001b[39m \u001b[43mresult\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mpois\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[0;32m     35\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(pois)):\n\u001b[0;32m     36\u001b[0m         poilist\u001b[38;5;241m.\u001b[39mappend(pois[i])\n",
      "\u001b[1;31mKeyError\u001b[0m: 'pois'"
     ]
    }
   ],
   "source": [
    "if __name__ == \"__main__\":\n",
    "    # 替换为你的高德地图API密钥\n",
    "    api_key = '0f2c1ec37c25bb500e07f4898275c6e0'\n",
    "    # 搜索关键词和城市\n",
    "    keyword = '高校'\n",
    "    city = '武昌区'\n",
    "\n",
    "    # 获取POI数据\n",
    "    poi_data = get_poi_data(keyword, city, api_key)\n",
    "\n",
    "    # 数据预处理\n",
    "    df = preprocess_data(poi_data)\n",
    "\n",
    "    # 核密度分析\n",
    "    kernel_density_analysis(df)\n",
    "\n",
    "    # 探索性空间数据分析\n",
    "    # exploratory_spatial_data_analysis(df)"
   ]
  }
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